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For me the podcast is one of the few things that I really like. The philosophical discussions allow to get a glimpse of the mind of the interviewed person. Sometimes I'm quite shocked that some people seem so superficial - from a philosophical point of view - even when they belong to the best in their field.
The quality of the guests is amazing but the host is extremely off-putting and difficult to listen to.
I find that Lex often side-steps technical depth and wanders into the philosophical side of things. He has the opportunity to ask diving questions but he simply scratches the surface with nearly every guest. It's not entirely his fault, he's under time constraints but I'd hope for more intellectual stimulation. That said, I do appreciate his efforts and he seems like a genuinely nice fella.
I don’t know, i really like these forays into the philosophical.
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I believe this is overstated and makes it sound like all of his work is bs, when the majority of the book is just fine. (I could be wrong and would be happy to be proven so. Just not a fan of the all-or-nothing attitude people apply toward this book when that doesn't seem warranted.)
If some data is wrong and you can't tell which is which, how can you trust just some parts of this book? Are we to fact-check bit by bit until everything gets sorted out and we know for sure what parts of the book to trust? Besides, why go through all that trouble if there are heaps of good psychology books out there that aren't plagued with errors as this one? Since our time is so limited, I think it is a good heuri…
However, I don't think this justifies dismissing the entire book. "I'm not sure which studies weren't reproducible and I don't feel like looking them up," is a very different statement than, "This whole book is bullshit." There's really no reason to make that latter overstatement.
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I've heard something similar here on HN before (still didn't read the book myself), and what baffles me: wasn't he awarded the Nobel Prize for that work? Are those just political bullshit nowdays as well, like Oscars?
Sveriges Riksbank Prize in Economic Sciences (in memoriam of Alfred Nobel); not The Nobel Prize. Economics is mostly a set of shaggy dog stories in service of ideology, rather than a branch of legitimate scientific inquiry. I mean Paul Krugman won the same prize; he appears to be have a Brier score of 1 on his predictions.
Listen to a few of Lex's podcasts (his own and his appearance on Joe Rogan) before you dismiss his interviewing style and/or tone. You may very well learn to appreciate it and his breadth of technical knowledge as much as the quality of his guests, which probably the highest of any technical podcast so far.
Lex here. Thank you for this. Words of criticism can hurt pretty bad these days, so this kind of support really helps. Thank you.
Of course, I'm sure you don't feel untouchable, but maybe there is a certain cold comfort in knowing that inconsiderate criticism is a hallmark of becoming an institution. Keep up the good work, man.
Keep up the good work lex. The quantity of content you put out at the level of quality you do is very impressive.
Readings books is awesome because you are getting the condensed knowledge that someone have spend maybe decades of their lives to compile. When I listen to a podcast the same applies to a lesser extend. The problem is Lex does not ask interesting questions. He dwells into philosophical and common questions i.e "What is the meaning of life", "is math invented or discovered". This questions are interesting but are not in the guest field of expertise which in turn causes them to give a generic response. This devalues the quality of the podcast.
I am not sure if this is covered in the podcast, but from the title, I wonder if in deep neural net research there are papers and implementations of a system 1 and 2 like model. One part of the neural net could be system 1 for fast decision making, and other could be system 2, with more deliberate analysis. They could communicate over some shared medium.
Model free (system 1) is fast, stimulus-response mappings. In ML, these mappings are called a policy. Most of reinforcement learning, including deep-learning-based RL, is model free.
Model-based (system 2) is less widely used. In this case, an agent or system is trying to learn the dynamics of a system and use those to project or forecast into the future. This is really helpful for e.g. learning a control system. Being able to use a model of the world to make accurate predictions lets you plan.
Thank you Lex. I think your podcast are the most interesting in the internet. But... Readings books is awesome because you are getting the condensed knowledge that someone have spend maybe decades of their lives to compile. When I listen to a podcast the same applies to a lesser extend. The problem is Lex does not ask interesting questions. He dwells into philosophical and common questions i.e "What is the meaning of…
My advice would be to ask shorter questions, sometimes Lex you try to explain what you mean. I would just drop the question and let the other person start talking instead of you trying to fill the silence.
Also I do really enjoy the questions about meaning of life (maybe more discussions on free will would be great too).
In any case, hats off to you Lex for interviewing some of the most interesting people in the field (and those who are not exactly in the field too).
Also I love how you show up with a suit.